Anti-bullying interventions at school: aspects of programme adaptation and critical issues for further programme development
Bibliographic record
Abstract
Recently, a growing interest in problems at school of peer aggression and victimization was observed. As a result, intervention strategies appropriate for this kind of problem were required. The Norwegian anti-bullying intervention that was developed and evaluated by Olweus (1992) in the region of Bergen was considered to be a good model for other countries to implement interventions against peer aggression within the school environment. It was therefore adapted to the educational settings of other countries. This paper aims to discuss the adaptation processes of the Bergen anti-bullying programme and to give guidelines to advance further programme development. For this, the DFE Sheffield Bullying Project (Smith and Sharp, 1994), the Anti-bullying Intervention in Toronto schools (Pepler et al., 1994) and the Flemish anti-bullying project (Stevens and Van Oost, 1994) were considered in the analyses. Discussion of the adaptation processes of the Bergen model programme revealed that the adapted interventions largely succeeded in incorporating the core components of the Bergen model programme, taking into account the characteristics of the implementation environment. This suggests that for bully/victim interventions, the dilemma of programme fidelity and programme adaptation could be solved adequately. However, from a health promotion perspective, some critical issues for programme improvement were observed. Three suggestions for change were made, indicating that anti-bullying actions at schools may benefit from: (i) a clear overview of the learning objectives, specified per target population; (ii) more attention to parental involvement and family interventions; and (iii) additional information about the adoption processes of the anti-bullying interventions within schools.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.208 | 0.195 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".